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Record W7135769001

Independence and Transmission of Monetary Policy in Small Open Economies: The Case of Canada and the Czech Republic

2022· dissertation· en· W7135769001 on OpenAlexaboutno aff
Jan Budinský

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2022
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsMonetary policyInflation targetingCurrencyInflation (cosmology)CzechCointegrationMonetary baseIndependence (probability theory)Small open economy
DOInot available

Abstract

fetched live from OpenAlex

The question of whether a small open economy (SOE) with highly integrated financial markets can shield itself from the influence of foreign monetary policy and preserve its monetary independence has been the subject of extensive research over the last decades. The growing integration of world economies owing to globalization, the impacts of recent global pandemic on them leading to the use of unconventional monetary policies, and the consequent high levels of inflation across the globe have highlighted the importance of further study of this problematic. This thesis focuses on two small open economies from different currency areas, Canada and the Czech Republic, and evaluates the monetary policies of their central banks, concentrating primarily on their independence, secondarily on the transmission mechanism of the respective policies, and also on their foreign exchange reserves. A comparative analysis of these two countries and their monetary policies on such scale and complexity has not yet been made before. The results of cointegration testing of vector autoregression models consisting of three-month interbank interest rates representing the monetary policies of the countries under investigation revealed that both Canada and the Czech Republic exhibited a considerable degree of monetary...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.004
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.220
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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